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Load Frequency Control of Distributed Generators Assisted Hybrid Power System Using QOHSA Tuned Model Predictive Control

Authors :
Akshay Kumar
Neetu Kumari
Gauri Shankar
Rajvikram Madurai Elavarasan
Sachin Kumar
Ankit Kumar Srivastava
Baseem Khan
Source :
IEEE Access, Vol 10, Pp 109311-109325 (2022)
Publication Year :
2022
Publisher :
IEEE, 2022.

Abstract

One of the challenging issues in a hybrid power system (HPS) is to provide a stable power supply with minimum frequency deviation, which can be accomplished by ensuring a coordinated operation among intermittent type distributed generators (DGs). In this study, the coordinated operation of a tidal turbine generator (TTG) (an emerging and less explored DG), diesel engine generator (DEG) and plug-in hybrid electric vehicles (PHEVs) based an autonomous HPS (a less explored HPS of this kind) for load frequency control (LFC) is investigated. The coordinated operation of different control loops such as the blade pitch control loop of TTG, supplementary control loop of DEG, and power control loop of PHEVs are realized through the maiden application of the proposed quasi-oppositional harmony search algorithm (QOHSA) based model predictive control (MPC) strategy. To establish the superiority of the proposed QOHSA tuned MPC method in mitigating frequency deviation following disturbance, its performance is compared with that of the coordinated performance obtained using QOHSA tuned conventional controllers and other existing optimization algorithms. The results conclude that the suggested method can significantly reduce frequency fluctuation under different load disturbances. The proposed method can handle different variances of the disturbance signals or noise entering the system as well as the model mismatch.

Details

Language :
English
ISSN :
21693536
Volume :
10
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.0f9745b4deac40d6950401141042036d
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2022.3214315